The University of Maryland (UMD) has announced the launch of the Quantum Technology Center (QTC), which aims to translate quantum physics research into innovative technologies.

The center will capitalize on the university’s strong research programs and partnerships in quantum science and systems engineering, and pursue collaborations with industry and government labs to help take promising quantum advances from the lab to the marketplace. QTC will also train students in the development and application of quantum technologies to produce a workforce educated in quantum-related engineering.

The launch of QTC comes at a pivotal time when quantum science research is expanding beyond physics into materials science, engineering, computer science, chemistry, and biology. Scientists across these disciplines are looking for ways to exploit quantum physics to build powerful computers, develop secure communication networks, and improve sensing and imaging capabilities. In the future, quantum technology could also impact fields such as artificial intelligence, energy, and medicine.

Fearless vision

The rules of quantum physics cover the shockingly strange behaviors of atoms and smaller particles. Technologies based on the first century of quantum physics research are close at hand in your daily life—in your smartphone’s billions of transistors and GPS navigation, for instance.

UMD has long been a powerhouse in quantum research and is now accelerating this trend with the launch of QTC. Founded jointly by UMD’s A. James Clark School of Engineering and College of Computer, Mathematical, and Natural Sciences, QTC will translate quantum science to the marketplace.

“QTC will be a community that brings together different types of people and ideas to create new quantum technologies and train a new generation of quantum workforce,” says QTC founding Director Ronald Walsworth. “UMD will focus on developing these technologies in the early stages, and then translating them out to the wider world with diverse partners.”

Like UMD’s existing quantum research programs, QTC is expected to draw strong sponsorship from federal research agencies. National support for quantum research is on the upswing—most notably evidenced by the National Quantum Initiative, signed into law in December 2018, which authorizes $1.275 billion over five years for research.

Quantum research on the rise

UMD already hosts more than 200 researchers in quantum science, one of the greatest concentrations in the world. Much of the effort has been led by the Joint Quantum Institute (JQI) and Joint Center for Quantum Information and Computer Science (QuICS), both partnerships between UMD and the National Institute of Standards and Technology. JQI and QuICS support many projects that cross boundaries in research disciplines and organizations; this trend will only increase with QTC on campus.

One prime example of constructively blurred lines comes from the research of Distinguished University Professor Chris Monroe. An international leader in isolating individual atoms for quantum computing and simulation, Monroe is a member of all three centers, and well-positioned to tap into the expertise of researchers in related disciplines.

Professor Edo Waks and Associate Professor Mohammad Hafezi, both members of QTC and JQI, are also among the UMD researchers helping to form the next revolution of quantum research with groundbreaking work on devices for quantum information processing and quantum networks.

Mohammad Hafezi and team have created the first silicon chip that can reliably constrain light to its four corners. Image: E. Edwards/JQI.

“Using our transistor, we should be able to perform quantum gates between photons,” says Waks. “Software running on a quantum computer would use a series of such operations to attain exponential speedup for certain computational problems.”

“We have been developing integrated silicon photonic systems to realize ideas derived from topology in a physical system,” Hafezi says. “The fact that we use components compatible with current technology means that, if these systems are robust, they could possibly be translated into immediate applications.”

Grounding a quantum community

“QTC will be a crucible for quantum science and engineering,” says Walsworth, a leader in quantum sensing who was recruited from Harvard University to lead the new center. “We’ll be building bridges between people, between sectors, between theories and technologies. There’s a kind of hunger for a community that pulls people together to pool information and find ways to overcome challenges in this exciting new area.”

According to Clark School Dean and Farvardin Professor Darryll Pines, UMD’s hiring of Walsworth signals an important next step in bringing engineering solutions to the forefront. “He’s the perfect representative to bridge the gap between physics and engineering, because he's already been doing that himself,” says Pines.

In addition to his broad range of research accomplishments, Walsworth has acted as an advisor for corporations and co-founded two companies based in part on his lab’s work. Quantum Diamond Technologies is developing applications in medical diagnostics for quantum measurement technologies that can be generated at room temperatures in synthetic diamonds. Hyperfine Research is creating low-cost portable MRI machines.

“If you really want a new community of technology to flourish, you’ve got to have the applications right,” Walsworth adds. “You've got to be solving someone's problems. Some people are busy building their technologies, but they don’t always know what the technologies are good for. Other people are out there complaining about how they can't solve their problems, but they don't know what technology exists that might help.”

Making the match will require QTC researchers to seek out groups across and outside the university to talk about actual challenges where quantum technology might help.

“From a United States perspective, this is a big deal,” he says. “Quantum is one of those areas that requires enormous investment from the federal government, to advance our knowledge in this space. We hope this leads to opportunities that translate to real products with positive impact for people, society, and the U.S. economy.”

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here’s what we have so far (send us your events!):

Let us know if you have suggestions for next week, and enjoy today’s videos.

Team PLUTO (University of Pennsylvania, Ghost Robotics, and Exyn Technologies) put together this video giving us a robot’s-eye-view (or whatever they happen to be using for eyes) of the DARPA Subterranean Challenge tunnel circuits.

Zhifeng Huang has been improving his jet-stepping humanoid robot, which features new hardware and the ability to take larger and more complex steps.

This video reported the last progress of an ongoing project utilizing ducted-fan propulsion system to improve humanoid robot’s ability in stepping over large ditches. The landing point of the robot’s swing foot can be not only forward but also side direction. With keeping quasi-static balance, the robot was able to step over a ditch with 450mm in width (up to 97% of the robot’s leg’s length) in 3D stepping.

This is one reason we should pursue not “autonomous cars” but “fully autonomous cars” that never require humans to take over. We can’t be trusted.

During our early days as the Google self-driving car project, we invited some employees to test our vehicles on their commutes and weekend trips. What we were testing at the time was similar to the highway driver assist features that are now available on cars today, where the car takes over the boring parts of the driving, but if something outside its ability occurs, the driver has to take over immediately.

What we saw was that our testers put too much trust in that technology. They were doing things like texting, applying makeup, and even falling asleep that made it clear they would not be ready to take over driving if the vehicle asked them to. This is why we believe that nothing short of full autonomy will do.

Buddy is a DIY and fetchingly minimalist social robot (of sorts) that will be coming to Kickstarter this month.

We have created a new arduino kit. His name is Buddy. He is a DIY social robot to serve as a replacement for Jibo, Cozmo, or any of the other bots that are no longer available. Fully 3D printed and supported he adds much more to our series of Arduino STEM robotics kits.

Buddy is able to look around and map his surroundings and react to changes within them. He can be surprised and he will always have a unique reaction to changes. The kit can be built very easily in less than an hour. It is even robust enough to take the abuse that kids can give it in a classroom.

The android Mindar, based on the Buddhist deity of mercy, preaches sermons at Kodaiji temple in Kyoto, and its human colleagues predict that with artificial intelligence it could one day acquire unlimited wisdom. Developed at a cost of almost $1 million (¥106 million) in a joint project between the Zen temple and robotics professor Hiroshi Ishiguro, the robot teaches about compassion and the dangers of desire, anger and ego.

What a package of medicine sees while being flown by drone from a hospital to a remote clinic in the Dominican Republic. The drone flew 11 km horizontally and 800 meters vertically, and I can’t even imagine what it would take to make that drive.

My first ride in a fully autonomous car was at Stanford in 2009. I vividly remember getting in the back seat of a descendant of Junior, and watching the steering wheel turn by itself as the car executed a perfect parking maneuver. Ten years later, it’s still fun to watch other people have that experience.

Flirtey, the pioneer of the commercial drone delivery industry, has unveiled the much-anticipated first video of its next-generation delivery drone, the Flirtey Eagle. The aircraft designer and manufacturer also unveiled the Flirtey Portal, a sophisticated take off and landing platform that enables scalable store-to-door operations; and an autonomous software platform that enables drones to deliver safely to homes.

EPFL scientists are developing new approaches for improved control of robotic hands – in particular for amputees – that combines individual finger control and automation for improved grasping and manipulation. This interdisciplinary proof-of-concept between neuroengineering and robotics was successfully tested on three amputees and seven healthy subjects.

Founder and Head of Product, Ian Bernstein, and Head of Engineering, Morgan Bell, have been involved in the Misty project for years and they have learned a thing or two about building robots. Hear how and why Misty evolved into a robot development platform, learn what some of the earliest prototypes did (and why they didn’t work for what we envision), and take a deep dive into the technology decisions that form the Misty II platform.

This week’s CMU RI Seminar is from Ross Knepper at Cornell, on Formalizing Teamwork in Human-Robot Interaction.

Robots out in the world today work for people but not with people. Before robots can work closely with ordinary people as part of a human-robot team in a home or office setting, robots need the ability to acquire a new mix of functional and social skills. Working with people requires a shared understanding of the task, capabilities, intentions, and background knowledge. For robots to act jointly as part of a team with people, they must engage in collaborative planning, which involves forming a consensus through an exchange of information about goals, capabilities, and partial plans. Often, much of this information is conveyed through implicit communication. In this talk, I formalize components of teamwork involving collaboration, communication, and representation. I illustrate how these concepts interact in the application of social navigation, which I argue is a first-class example of teamwork. In this setting, participants must avoid collision by legibly conveying intended passing sides via nonverbal cues like path shape. A topological representation using the braid groups enables the robot to reason about a small enumerable set of passing outcomes. I show how implicit communication of topological group plans achieves rapid covergence to a group consensus, and how a robot in the group can deliberately influence the ultimate outcome to maximize joint performance, yielding pedestrian comfort with the robot.

In this week’s episode of Robots in Depth, Per speaks with Julien Bourgeois about Claytronics, a project from Carnegie Mellon and Intel to develop "programmable matter."

Julien started out as a computer scientist. He was always interested in robotics privately but then had the opportunity to get into micro robots when his lab was merged into the FEMTO-ST Institute. He later worked with Seth Copen Goldstein at Carnegie Mellon on the Claytronics project.

Julien shows an enlarged mock-up of the small robots that make up programmable matter, catoms, and speaks about how they are designed. Currently he is working on a unit that is one centimeter in diameter and he shows us the very small CPU that goes into that model.

THE INSTITUTEDementia affects millions of people worldwide. There is no treatment, but an early diagnosis can help patients slow the progress of their symptoms. The condition can affect people’s mental function, behavior, and memory.

Because dementia can cause different patterns of damage to the brain, no single test can determine whether someone has it. Instead, doctors use several screening tools including in-person interviews, questionnaires about daily routines, and drawing assessments. The tests, performed by clinicians and other professionals, are done regularly to check for changes—which can become expensive.

IEEE Fellow Helen Meng, a professor of systems engineering and engineering management at the Chinese University of Hong Kong (CUHK), is working on a machine-learning platform to helpmake screening more accessible and less expensive. The platform likely will use data analytics, human-computer interaction, and spoken-language technology.

Hong Kong has a large aged population, Meng says, and dementia is on the rise. Although all the region’s citizens are covered by the public health care system, it can take a long time to get an appointment with a specialist, she says, so valuable time can be lost. She is working with other researchers at the university, including many IEEE members, to make assessments accessible through AI, and eventually give people the ability to do self-assessments.

“As a researcher, a lot of our efforts have been focused on advances in existing applications such as high-accuracy speech recognition,” Meng says, “but I want to look into using the technology for new applications such as detecting early signs of dementia. The way to catch dementia early is to do frequent assessments on an individual’s capabilities. If dementia can be detected earlier, intervention can be started sooner.”

ASSESSMENT TESTS

One well-known exam that neurologists perform is the Montreal Cognitive Assessment. Designed to evaluate short-term memory, language ability, and attention span, it includes activities such as naming animals and drawing components of a clock. As with other such assessments, the Montreal test is still done on paper, and the results are not digitized.

The neurologist interviews patients and asks them to assess their memory and cognitive functions. The patients’ responses might be subjective, varying from day to day even if their abilities don’t.

Meng says machine learning and big data can help make those diagnoses more objective. Artificial intelligence algorithms and other technology could automatically analyze collected data.

In particular, spoken-language technology could be used to assess a person’s cognitive health and emotional state based on their speech.

“We want to be able to identify spoken-language biomarkers that are indicative of neurocognitive disorders,” Meng says. “The reaction time after a question is asked could be recorded. For example, if there’s a lot of hesitation or pausing, even at millisecond intervals, these could be measured in an objective way using engineering approaches.”

Offering tests on a computer or recording people’s speech while they answer questions via a telephone could help reduce the number of needed visits to the doctor, Meng says. A clinical cognitive expert or neurologist would review the automated assessments.

“We don’t intend for our automated software to make decisions about whether someone has dementia,” she says. “Our objective is not to replace the clinicians. We look at AI as a decision-support tool.”

The project has recently been awarded the theme-based research scheme of Hong Kong’s Research Grants Council. This is among the highest level of research funding in the region, according to Meng.

Photo: The Chinese University of Hong Kong

Meng recently spoke on the topic of artificial intelligence and well-being as part of a lecture series at the Chinese University of Hong Kong.

COMBINING TWO PASSIONS

Meng, who grew up in Hong Kong, was accepted to medical school as well as MIT’s engineering program. She says she thought it would be a good experience to study abroad, so she attended MIT, where she earned bachelor’s and master’s degrees in electrical engineering. She also got a Ph.D. in electrical engineering and computer science there.

“IEEE is a global platform, so there are many ways to participate,” she says. “I’ve made quite a few friends and met colleagues around the world who are experts in their area. It has been a great experience.

“Membership also broadens one’s horizons. Through IEEE’s conferences and publications, you get to look beyond your own area of expertise.”

Meng works to increase the number of women in engineering. She and other women have spoken during the annual IEEE Signal Processing Society conference’s luncheon.

“We make sure that female keynote speakers are invited to conferences, not just men,” she says. “We need more gender diversity.”

In software development, a common metric called code coverage measures the percentage of a system’s code that is covered by tests performed prior to deployment. Code coverage is typically measured automatically by a separate software program, or it can be invoked manually from the command line for certain code coverage tools. The results show exactly which lines of code were executed when running a test suite, and could reveal which lines may need further testing.

Ideally, software development teams aim for 100 percent code coverage. But in reality, this rarely happens because of the different paths a certain code block could take, or the various edge cases that should (or shouldn’t) be considered based on system requirements.

Illustration: Google
More projects at Google have actively incorporated automated code coverage tools in recent years.

Measuring code coverage has become common practice for software development and testing teams, but the question of whether this practice actually improves code quality is still up for debate.

Some argue that developers might focus on quantity rather than quality, creating tests just to satisfy the code coverage percentage instead of tests that are robust enough to identify high-risk or critical areas. Others raise concerns about its cost-effectiveness—it takes valuable developer time to review the results and doesn’t necessarily improve test quality.

For a large organization such as Google—with a code base of one billion lines of code receiving tens of thousands of commits per day and supporting seven programming languages—measuring code coverage can be especially difficult.

A recent study led by Google AI researchers Marko Ivanković and Goran Petrović provides a behind-the-scenes look at the tech giant’s code coverage infrastructure, which consists of four core layers. The bottom layer is a combination of existing code coverage libraries for each programming language, while the middle layers automate and integrate code coverage into the company’s development and build workflows. The top layer deals with visualizing code coverage information using code editors and other custom tools.

As part of the study, Ivanković and Petrović analyzed code coverage adoption rates over a five-year period. They found that despite code coverage not being mandatory at Google, the rate of adoption has grown steadily since 2014. In the first quarter of 2018, more than 90 percent of projects used automated code coverage tools.

The researchers also collected 512 survey responses from 3,000 randomly chosen Google developers and other employees in non-engineering roles on the usefulness of code coverage. Among the respondents, only 45 percent use code coverage frequently when authoring code changes, while 40 percent use it regularly when conducting code reviews.

Ivanković spoke to IEEE Spectrum about the study and the role code coverage plays in software development and testing.

This interview has been edited and condensed for clarity.

IEEE Spectrum: Why do you think code coverage is important?

Marko Ivanković: A lot of people are probably expecting us to say something along the lines of, “Good coverage reduces [the] number of bugs.” That’s certainly part of it, but one of the more surprising insights [we found] was that even if coverage wasn’t directly helpful as a quality signal, it would still be worth computing.

Coverage might not directly be helpful for humans looking at the code, but it would still be helpful for tools—for example, a tool that analyzes dependencies. So for instance, if code A declares that it depends on code B, but tests for code A never reach code B, then it’s possible that the dependency is not real, and an automated tool can try to remove it to simplify the code base.

Of course, actual implementation is much more complex than that. We’ve found dozens of such tools that can use coverage information provided by our infrastructure to improve their own functionality. And for many of these use cases, the correlation between code coverage and code quality is not at all important.

IEEE Spectrum: What inspired you to study code coverage at Google?

Ivanković: We were inspired by a problem we faced ourselves. During code reviews, we were spending a lot of time trying to figure out if the tests actually test the code or not. At the time, coverage computation was supported by the build system, but you had to manually invoke it and manually overlay the coverage results and the code you were reviewing. One day, we just said to ourselves, “There has to be a way to automate this.” After a week, we had the first prototype running. Other engineers saw it and asked if they could get the same. We wanted to make sure we were providing them with the best possible experience so we started researching the problem.

IEEE Spectrum: What surprised you most about your results?

Ivanković: We were surprised by the number of people who were originally skeptical of coverage that ended up adopting the methodology and ultimately finding it useful. A number of people we surveyed were against coverage on principle, but they still admitted to using it sometimes and finding it useful.

IEEE Spectrum: What's the biggest challenge you faced with your study, and how did you overcome it?

Ivanković: On the surface, code coverage appears to be a simple concept: A line is either covered by tests or it isn’t. But it turned out to be full of corner cases and unexpected situations when implemented at scale. It took us several years of hard work to fix all failure modes in the infrastructure.

We hit a similar challenge when we were conducting our study. Most engineers we surveyed had the same overall idea of what coverage is, but when asked for details, their responses differed widely. We had to try several surveys on smaller populations before we got the questions right.

IEEE Spectrum: What do you see as the strengths of Google's code coverage infrastructure? What else do you think could be improved?

Ivanković: We worked hard to make sure the infrastructure is resource-efficient and can run at Google’s massive scale. Showing people that it’s possible to do this is probably the biggest contribution [of our study].

We designed our infrastructure in a way that makes it easy to experiment, do A/B testing, and evaluate hypotheses. We also export all data in accessible formats so coverage can be visualized, which helps teams keep their code healthy and prepare fix-it events.

When we were surveying engineers, some of them had improvement suggestions for us, some of which could be interesting to explore. One of the more playful ones was to not show the coverage results if they were too good, so the engineers don’t get overconfident.

IEEE Spectrum: What advice would you give software development and testing teams looking to deploy code coverage or improve their existing code coverage efforts?

Ivanković: I think the most important advice we could give is to focus on their workflow. Don’t just deploy coverage, but make sure you integrate it in the developer workflow at the right place, where the results are most useful. In our experience, code review is the cornerstone of code health.

IEEE Spectrum: What future developments are in store for Google’s code coverage infrastructure?

Ivanković: Currently, we’re looking further into the usage data and developer opinions to better understand how coverage is used. For example, we’re researching how the perceived usefulness differs from actual usefulness. A concrete question we would like to examine is, “Does showing coverage during code review actually speed up the review process?” The results of this research will determine our next infrastructure improvements.

In a paper appearing in Science Robotics this week, the roboticists behind AquaMAV present a fully operational robot that uses a solid-fuel powered chemical reaction to generate an explosion that powers the robot into the air.

The 2015 version of AquaMAV, which was mostly just some very vintage-looking computer renderings and a little bit of hardware, used a small cylinder of CO2 to power its water jet thruster. This worked pretty well, but the mass and complexity of the storage and release mechanism for the compressed gas wasn’t all that practical for a flying robot designed for long-term autonomy. It’s a familiar challenge, especially for pneumatically powered soft robots—how do you efficiently generate gas on-demand, especially if you need a lot of pressure all at once?

An explosion propels the drone out of the water

There’s one obvious way of generating large amounts of pressurized gas all at once, and that’s explosions. We’ve seen robots use explosive thrust for mobility before, at a variety of scales, and it’s very effective as long as you can both properly harness the explosion and generate the fuel with a minimum of fuss, and this latest version of AquaMAV manages to do both:

The water jet coming out the back of this robot aircraft is being propelled by a gas explosion. The gas comes from the reaction between a little bit of calcium carbide powder stored inside the robot, and water. Water is mixed with the powder one drop at a time, producing acetylene gas, which gets piped into a combustion chamber along with air and water. When ignited, the acetylene air mixture explodes, forcing the water out of the combustion chamber and providing up to 51 N of thrust, which is enough to launch the 160-gram robot 26 meters up and over the water at 11 m/s. It takes just 50 mg of calcium carbide (mixed with 3 drops of water) to generate enough acetylene for each explosion, and both air and water are of course readily available. With 0.2 g of calcium carbide powder on board, the robot has enough fuel for multiple jumps, and the jump is powerful enough that the robot can get airborne even under fairly aggressive sea conditions.

Image: Science Robotics
The robot can transition from a floating state to an airborne jetting phase and back to floating (A). A 3D model render of the underside of the robot (B) shows the electronics capsule. The capsule contains the fuel tank (C), where calcium carbide reacts with air and water to propel the vehicle.

Next step: getting the robot to fly autonomously

Providing adequate thrust is just one problem that needs to be solved when attempting to conquer the water-air transition with a fixed-wing robot. The overall design of the robot itself is a challenge as well, because the optimal design and balance for the robot is quite different in each phase of operation, as the paper describes:

For the vehicle to fly in a stable manner during the jetting phase, the center of mass must be a significant distance in front of the center of pressure of the vehicle. However, to maintain a stable floating position on the water surface and the desired angle during jetting, the center of mass must be located behind the center of buoyancy. For the gliding phase, a fine balance between the center of mass and the center of pressure must be struck to achieve static longitudinal flight stability passively. During gliding, the center of mass should be slightly forward from the wing’s center of pressure.

The current version is mostly optimized for the jetting phase of flight, and doesn’t have any active flight control surfaces yet, but the researchers are optimistic that if they added some they’d have no problem getting the robot to fly autonomously. It’s just a glider at the moment, but a low-power propeller is the obvious step after that, and to get really fancy, a switchable gearbox could enable efficient movement on water as well as in the air. Long-term, the idea is that robots like these would be useful for tasks like autonomous water sampling over large areas, but I’d personally be satisfied with a remote controlled version that I could take to the beach.

Transmission lines in the United States and Canada require approval from every state and province traversed, and that political fragmentation hinders deployment of long power links of the type connecting vast swaths of territory in regions such as China, India, and Brazil. As a result, few studies detail how technologies that efficiently move power over thousands of kilometers, such as ultrahigh-voltage direct current (UHV DC) systems, might perform in North America. Earlier this week, the Beijing-based Global Energy Interconnection Development and Cooperation Organization (GEIDCO) stepped in to fill that gap, outlining an ambitious upgrade for North America’s grids.

GEIDCO’s plan promises to greatly shrink North America’s carbon footprint, but its boldest prescriptions represent technical and economic optimizations that run counter to political interests and recent trends. “Thinking out of the box is how you solve complicated, difficult problems,” said former Southern California Edison CEO Ted Craver in response to the plan. But GEIDCO’s approach, he said, raises concerns about energy sovereignty that could prove difficult to settle. As Craver put it: “There’s theory and then there’s practice.”

Through GEIDCO, Liu is proselytizing for UHV deployment worldwide. At the Vancouver meeting, Liu warned of “unimaginable damage to mankind” if greenhouse gas emissions continued at their current pace. He argued that beefy grids moving power across and between continents are a prerequisite for accessing and sharing the world’s best wind, solar, and hydropower resources, and thus dialing-down fossil fuel consumption.

GEIDCO’s plan for North America mirrors the combination of UHV AC and DC transmission deployed by State Grid in China. In that scheme, a series of 800-kV UHV DC lines running east to west across the U.S. would share wind and solar power widely, while north-south lines would provide continent-wide access to Canada’s giant hydropower plants [see map below]. One more UHV DC line—a 5,200-kilometer stretch from Mexico to Peru—would enable power exchanges with South America.

As in China, UHV AC lines would be added atop North America’s five existing AC grids, strengthening them so they could safely absorb the 8-gigawatt output of each DC line. In two cases, UHV AC would eventually cross boundaries between distinct AC grids to create larger and more stable synchronous zones: Mexico’s grid would fold into the larger grid that currently covers the Western U.S. and Canada; and Texas’ grid would merge with North America’s big Eastern grid.

Consolidating grids helps explain the benefit of GEIDCO’s plan. Texas’ grid is only weakly linked to its neighbors at present, which limits its ability to share resources such as extra wind power that may go to waste for lack of in-state demand or to important renewable power when its wind farms are still. GEIDCO’s UHV build-out unlocks such resources by enabling each power plant to serve a larger area.

The payoffs are numerous. Electrification to decarbonize vehicles, home heating, and industries would proceed 60 percent faster than the most ambitious U.S. electrification scenarios projected by the Electric Power Research Institute. Renewable energy installation would also accelerate, pushing the share of zero-carbon energy on the continent from 40 percent of the power supply in 2017, to 64 percent in 2035, and 74 percent in 2050. Nuclear energy’s contribution would fall by nearly half to just 11 percent of generation in 2050—mostly due to its higher cost, according to GEIDCO director of energy planning Gao Yi. Overall, energy-related greenhouse gas emissions would drop 80 percent by 2050, relative to a business-as-usual scenario—even as average power generating costs drop.

However, consolidating grids is also where the political sensitivity begins. Texas fiercely guards its independent AC grid, which shields its power industry from oversight by federal regulators. Craver’s take on the prospects for bringing Texas into the fold: “Good luck on that.”

Broader political concerns, meanwhile, could hold up international UHV links. Deeper integration of power supplies across borders implies a high level of trust between nations. That cuts against the recent trend toward populist governments advocating more nationalist agendas, as exemplified by the U.K.’s ongoing effort to leave the European Union.

A populist Mexican President elected last year has blocked international investment in renewable energy and could undo recent efforts to expand the country’s grid interconnections. U.S. President Trump has decreased trust in the United States as an international partner with his America-first trade policies and plans to withdraw the U.S. from global pacts such as the Paris Agreement on Climate Change.

At the Vancouver forum, organized by the Edison Electric Institute, a Washington-based trade group, most grid experts identified politics and social acceptance as the greatest challenges to power network expansion. In the U.S., climate and energy policy has made it more difficult for government researchers to even study North American grid integration.

Last year, political appointees at the U.S. Department of Energy blocked publication of a modeling study exploring integration of the Eastern and Western grids via DC lines. The study, led by the grid modeling group at the National Renewable Energy Lab (NREL) in Boulder, Colo., projected that long DC lines linking the grids would reduce power costs and accelerate renewable energy development. According to the study’s leader, it showed that “building national-scale transmission makes sense.”

NREL’s grid modelers are now wrapping up a larger continent-wide study looking at the challenges and opportunities for grid integration of very large levels of wind, solar and hydropower. That North American Renewable Integration Study is a collaborative effort by the U.S., Mexican, and Canadian governments. It was supposed to be completed this month, but remains under review by the three governments.